Save moneywhile saving the environment.
Set ready-by times for EV charging, laundry and water heating. GreenAI finds lower-carbon windows on your local grid and schedules each task before its deadline.
Tonight's plan
Optimized32% less carbon tonight
ready by 7:00a
- 35%
- High End Household Carbon Reduction.
- $350
- Average bill savings in NJ.
- And all smart devices controlled in one app.
01 / The Problem
Household demand peaks after solar generation peaks.
Millions of households charge cars after work and run dishwashers after dinner, as solar generation falls. Grid operators dispatch higher-emission plants to meet that evening demand and may curtail solar at midday when demand cannot absorb the available supply.
- 01
12 PM
Midday solar approaches demand.
23,074 MW solar against 25,063 MW of demand.
- 02
7 PM
Evening demand peaks as solar falls.
36,080 MW demand, with solar down to 7,271 MW.
- 03
8 PM
Demand stays high as solar falls to 188 MW.
At 8 PM, demand remains 35,011 MW.
- 04
2 AM
GreenAI moves the flexible load out of that gap.
The same charge, run in the overnight hours instead of the evening peak.
Hourly MW, CAISO, June 15 2026
One recorded CAISO day. Hourly averages. Small negative overnight solar readings are clamped to 0 for display. Read the methodology and limitations.
Reading the chart
California's peak demand occurs hours after peak solar generation. Grid operators dispatch natural gas plants and other carbon-heavy generators to serve demand outside peak solar hours. Households can cut emissions and ease peak demand by moving flexible energy use to lower-carbon grid hours. GreenAI schedules those shifts around device deadlines.
02 / Device scheduling
GreenAI schedules devices by grid carbon intensity.
You set a ready-by time for each device. GreenAI uses your local grid's hourly emissions data to schedule flexible energy use before the deadline.
EV Charger
1:20a–5a
Dishwasher
1:45a–6a
Water Heater
3:40a–4:40a
HVAC
8p–10p
Washer
no run
Simulated schedule for the prototype household. Device times and the carbon curve are illustrative, not measured. GreenAI holds each run inside the 12:00 AM–6:00 AM clean window unless a comfort deadline puts it elsewhere.
- 01
Grid carbon by hour
GreenAI compares carbon-intensity data from Electricity Maps with household load profiles from NREL ResStock to identify lower-carbon hours.
- 02
Cross-brand scheduling
GreenAI schedules EV charging and connected appliances across manufacturers through platforms such as SmartThings.
- 03
Ready-by scheduling
You set a ready-by time. GreenAI chooses a lower-carbon window that meets the deadline.
- 04
Virtual power plant
GreenAI can coordinate load shifts across thousands of participating households to reduce peak demand and the need for standby generation.
35%reduction
in carbon emissions for a simulated household when GreenAI moves flexible loads to lower-carbon hours.
Modeled reduction: 35 of 100 household-emissions units
We modeled household load-shifting with CAISO hourly emissions data. No GreenAI field deployment has measured this result.
03 / The Product
Try the prototype live
That's the prototype's own dashboard, drawn from the same device list and the same CAISO day this page charts rather than from a screenshot. Open it and the schedules, the deadlines and the grid-cleanliness readout all run live in your browser. The only thing missing is the connection to a real home.
GreenAI is coordinating 4 of 5 devices in this simulation. Grid carbon intensity is in the excellent band.
Next clean window · 12:00 AM–6:00 AM
Simulated CO₂e avoided today
6.8 kg
a simulated high-impact clean-grid day
Your devices
EV Charger
Paused at 62%, resumes 1:20a
Dishwasher
Scheduled 1:45a, ready 6:00a
Water Heater
Heating now, in clean window
HVAC
Pre-cooling held until 8:00p
Washer
Idle, nothing scheduled